Like other image-recognition programs, the graffiti matching system searches for matches based on commonalities, according to Jain and his colleagues. This helps filter different graffiti that depicts the same logo or tag, but may look dramatically different based on the person or gang who created it. First, the system extracts visual features from a new image, and then letters, numbers and symbols are manually annotated. Then, the system finds candidate images that share similarities with this new image.

It would be nice to have a system that automatically recognizes numbers and letters, but this is too difficult with existing technology because graffiti is so variable, Jain and his colleagues say. Instead, Jain uses crowdsourcing to identify words, using Amazon’s Mechanical Turk service, according to New Scientist.

In the march toward our ubiquitous automated surveillance future…

(Source: murketing)